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1,069 results for “Data managment”
Data Publication accompanying the paper "Methods to Evaluate Lifecycle Models for Research Data Management"
<p>The publications listed in dlc.bib were collected in 2017 and analysed.<br> The xml representations can be found in raw<br> dlc.csv includes the data summary.<br> </p>
MarTREC UTC Data Management Plan Project Name: Green Technology Approach for Capturing Pollution Washed from Transportation Infrastructures Principal Investigator Name(s): Dr. Danuta Leszczynska
<p>This is an original data related to the project sponsored by the MarTREC UTC </p> <p>Title: Green technology Approach for Capturing Pollution Washed from Transportation Infrastructures</p> <p>PI: Dr. Danuta Leszczynska</p>
Supporting data : Waste management by ants: the enhancing role of larvae
<p>As part of the publication process of our article "Waste management by ants: the enhancing role of larvae", we shared on Zenobo.org the dataset which underpins our results.</p>
Data from: Modelling variability in the fire-response of an endangered bird to improve fire-management
Conservation managers regularly burn vegetation to regenerate habitat for fire-dependent species. When determining the time-since-fire at which to burn, managers model change in a species' occurrence over time, post-fire (fire-response curve) and identify the time-since-fire associated with decline in occurrence. However, where species exhibit variability in their fire-response across space, using a single fire-response curve to determine the timing of burns may lead to burning habitat at an inappropriate time-since-fire. We tested if elevation, local topography, soil properties, vegetation type or evapotranspiration affect the fire-response of the endangered mallee emu-wren Stipiturus mallee and its hummock-grass habitat Triodia scariosa in south-eastern Australia (n= 217). Previous work on the mallee emu-wren found a unimodal fire-response with decline in occurrence at ~30-50 years-since-fire and a time-window of occurrence of ~30 years. We found that time-since-fire and elevation interact to affect the mallee emu-wren fire-response. At high elevations (55-98 m), mallee emu-wrens declined in occurrence at ~50 years-since-fire, with a time-window of occurrence of 20-40 years. However, at low elevations (28-55 m), mallee emu-wrens showed no decline in occurrence with increasing time-since-fire with a time-window of occurrence of up to 107 years. Extent cover of Tall T. scariosa showed similar patterns to the mallee emu-wren, indicating that vegetation structure is a likely driver of variability in the mallee emu-wren fire-response. We speculate that the effect of low elevation is mediated by increased soil nutrient and water availability for key plants. We used our findings to map the appropriate time-since-fire at which to burn to regenerate habitat for the mallee emu-wren across the study-region. We recommend no burning for regeneration across one-third of potential habitat, because the mallee emu-wren showed no decline in occurrence in these areas. We recommend managers model variability in species' fire-responses across space to improve the timing of burns for regeneration.
Figure 1 from: Briney KA, Coates H, Goben A (2020) Foundational Practices of Research Data Management. Research Ideas and Outcomes 6: e56508. https://doi.org/10.3897/rio.6.e56508
Figure 1 Simple workflow diagram for a Western Blot.
Figure 2 from: Briney KA, Coates H, Goben A (2020) Foundational Practices of Research Data Management. Research Ideas and Outcomes 6: e56508. https://doi.org/10.3897/rio.6.e56508
Figure 2 Example folder structure and file naming convention for a research team.
Data from: Management and outcome of primary CNS lymphoma patients in the modern era. a LOC network study
Objective: Studies on primary CNS lymphoma (PCNSL) patients in the "real life" are scarce. Our objective was to analyze, in a nationwide population-based study, the current medical practice in the management of PCNSL. Methods: The LOC database prospectively records all newly diagnosed PCNSL from 32 French centers. Data of patients diagnosed between 2011-2016 were retrospectively analyzed. Results: We identified 1002 immunocompetent patients (43% aged>70 years, median KPS 60). First-line treatment was high-dose methotrexate-based chemotherapy in 92% of cases, with an increasing use of rituximab over time (66%). Patients <60 years old received consolidation treatment in 77% of cases, consisting of whole-brain radiotherapy (WBRT) (54%) or high-dose chemotherapy with autologous stem cell transplantation (HCT-ASCT) (23%). Among the patients > 60 years old, WBRT and HCT-ASCT consolidation were administered in only 9% and 2%, respectively. The complete response rate to initial chemotherapy was 50%. Median progression-free survival was 10.5 months. For relapse, second-line chemotherapy, HCT-ASCT, WBRT and palliative care were offered to 55%, 17%, 10%, and 18% of patients, respectively. The median, 2-year and 5-year overall survival was 25.3 months, 51% and 38%, respectively (< 60 years: not reached (NR), 70% and 61%; > 60 years: 15.4 months, 44% and 28%). Age, KPS, sex and response to induction CT were independent prognostic factors in multivariate analysis. Conclusions: Our study confirms the increasing proportion of elderly within PCNSL and shows comparable outcome in this population-based study with those reported by clinical trials, reflecting a notable application of recent PCNSL advances in the real life.
Data from: Data management, archiving and sharing for biologists and the role of research institutions in the technology-oriented age
Data are one of the primary outputs of science. Although certain sub-disciplines of biology have pioneered efforts to ensure their long-term preservation and facilitate collaborations, data continue to disappear, owing mostly to technological, regulatory and ideological hurdles. In this review, we describe the important steps towards proper data management and archiving, and provide a critical discussion on the importance of long term data conservation. We then illustrate the rise in data archiving through the Joint Data Archiving Policy and the Dryad Digital Repository. In particular, we discuss data integration and how the limited availability of large scale datasets can hinder new discoveries. Finally, we propose solutions to increase the rate of data preservation. For example, by generating mechanisms insuring proper data management and archiving, by providing training in data management, and by transforming the traditional role of research institutions and libraries as data generators towards managers and archivers.
Data from: The effects of habitat management on the species, phylogenetic and functional diversity of bees are modified by the environmental context
Anthropogenic landscape elements, such as roadsides, hedgerows, field edges, and power line clearings, can be managed to provide important habitats for wild bees. However, the effects of habitat improvement schemes in power line clearings on components of diversity are poorly studied. We conducted a large-scale experiment to test the effects of different management practices on the species, phylogenetic, and functional diversity of wild bees in power line clearings (n = 19 sites across southeastern Norway) and explored whether any treatment effects were modified by the environmental context. At each site, we conducted the following treatments: (1) Cut: all trees cut and left to decay in the clearing; (2) Cut + Remove: all trees cut and removed from the plot; and (3) Uncut: uncleared. The site-specific environmental context (i.e., elevation and floral diversity) influenced the species, phylogenetic, and functional diversity within bee species assemblages. The largest number of species was found in the Cut + Remove treatment in plots with a high forb species richness, indicating that the outcome of management practices depends on the environmental context. Clearing of treatment plots with many forb species also appeared to alter the phylogenetic composition of bee species assemblages, that is, more closely related species were found in the Cut and the Cut + Remove plots than in the Uncut plots. Synthesis and applications: Our experimental simulation of management practices in power line clearings influenced the species, phylogenetic, and functional diversity of bee species assemblages. Frequent clearing and removal of the woody debris at low elevations with a high forb species richness can increase the value of power line clearings for solitary bees. It is therefore important for managers to consider the environmental context when designing habitat improvement schemes for solitary bees.
Data from: Avoiding tipping points in fisheries management through Gaussian process dynamic programming
Model uncertainty and limited data are fundamental challenges to robust management of human intervention in a natural system. These challenges are acutely highlighted by concerns that many ecological systems may contain tipping points, such as Allee population sizes. Before a collapse, we do not know where the tipping points lie, if they exist at all. Hence, we know neither a complete model of the system dynamics nor do we have access to data in some large region of state space where such a tipping point might exist. We illustrate how a Bayesian non-parametric approach using a Gaussian process (GP) prior provides a flexible representation of this inherent uncertainty. We embed GPs in a stochastic dynamic programming framework in order to make robust management predictions with both model uncertainty and limited data. We use simulations to evaluate this approach as compared with the standard approach of using model selection to choose from a set of candidate models. We find that model selection erroneously favours models without tipping points, leading to harvest policies that guarantee extinction. The Gaussian process dynamic programming (GPDP) performs nearly as well as the true model and significantly outperforms standard approaches. We illustrate this using examples of simulated single-species dynamics, where the standard model selection approach should be most effective and find that it still fails to account for uncertainty appropriately and leads to population crashes, while management based on the GPDP does not, as it does not underestimate the uncertainty outside of the observed data.
Data from: Real-world study of efficacy, risk management and reasons for discontinuation of natalizumab for treatment of multiple sclerosis in Russia
Background. NTZ is approved in Russia for the treatment of highly active relapsing remitting multiple sclerosis and is reimbursed via federal budget program. However, no data about NTZ treatment in Russia and the effect of federal reimbursement have been performed so far. Objective. To characterize the population of patients receiving natalizumab and assess the efficacy and risk-management plan (RMP) implementation of NTZ therapy in routine clinical practice in Russia. Methods. We analyzed data for 334 patients, who received at least one infusion of NTZ. Relapse rate, MRI activity, NEDA-3 status after 2 years were assessed. Anti-JC virus antibodies status and RMP implementation were evaluated. Drop-out rate and reasons for therapy discontinuation were analyzed. Results. Patients switched to natalizumab in Russia are mainly female (63%), with median EDSS score of 3.5 and high disease activity: 93% had at least 1 relapse and 58% had both T1Gd+ and new T2 lesion an year before therapy initiation. Introduction of federal reimbursement allowed to start therapy with natalizumab for patients with less relapses. The only predictor of 6-month progression was EDSS score at the baseline of therapy (HR=2.1375, 95%CI 1.0026 – 4.5570, p=0.0492). 82% patients reached NEDA-3 at 24 month of therapy. 25% of patients discontinued NTZ for reasons: tolerability (14.5%), JCV antibody status (61%), and patient's decision (17%). RMP was implemented in only 36% patients. Conclusion. Natalizumab appeared to have high efficacy in Russian clinical practice. Federal reimbursement allowed less active patients to start natalizumab. More efforts should be done to improve RMP implementation.
Data from: Management of pulmonary nodules by community pulmonologists
BACKGROUND: Pulmonary nodules (PNs) are a common reason for referral to pulmonologists. The majority of data for the evaluation and management of PNs is derived from studies performed in academic medical centers. Little is known about the prevalence and diagnosis of PNs, the use of diagnostic testing, or the management of PNs by community pulmonologists. METHODS: This multicenter observational record review evaluated 377 patients aged 40 to 89 years referred to 18 geographically diverse community pulmonary practices for intermediate PNs (8-20 mm). Study measures included the prevalence of malignancy, procedure/test use, and nodule pretest probability of malignancy as calculated by two previously validated models. The relationship between calculated pretest probability and management decisions was evaluated. RESULTS: The prevalence of malignancy was 25% (n = 94). Nearly one-half of the patients (46%, n = 175) had surveillance alone. Biopsy was performed on 125 patients (33.2%). A total of 77 patients (20.4%) underwent surgery, of whom 35% (n = 27) had benign disease. PET scan was used in 141 patients (37%). The false-positive rate for PET scan was 39% (95% CI, 27.1%-52.1%). Pretest probability of malignancy calculations showed that 9.5% (n = 36) were at a low risk, 79.6% (n = 300) were at a moderate risk, and 10.8% (n = 41) were at a high risk of malignancy. The rate of surgical resection was similar among the three groups (17%, 21%, 17%, respectively; P = .69). CONCLUSIONS: A substantial fraction of intermediate-sized nodules referred to pulmonologists ultimately prove to be lung cancer. Despite advances in imaging and nonsurgical biopsy techniques, invasive sampling of low-risk nodules and surgical resection of benign nodules remain common, suggesting a lack of adherence to guidelines for the management of PNs.
Data from: Survey design for precise fire management conservation targets
Common goals of ecological fire management are to sustain biodiversity and minimize extinction risk. A novel approach to achieving these goals determines the relative proportions of vegetation growth stages (equivalent to successional stages, which are categorical representations of time since fire) that maximize a biodiversity index. The method combines data describing species abundances in each growth stage with numerical optimization to define an optimal growth-stage structure which provides a conservation-based operational target for managers. However, conservation targets derived from growth-stage optimization are likely to depend critically on choices regarding input data. There is growing interest in use of growth-stage optimization as a basis for fire management, thus understanding of how input data influence the outputs is crucial. Simulated datasets provide a flexible platform for systematically varying aspects of survey design and species inclusions. We used artificial data with known properties, and a case-study dataset from southeastern Australia, to examine the influence of (i) survey design (total number of sites, and their distribution among growth stages) and (ii) species inclusions (total number of species and their level of specialization) on the precision of conservation targets. Based on our findings, we recommend that survey designs for precise estimates would ideally involve at least 80 sites, and include at least 80 species. Greater numbers of sites and species will yield increasingly reliable results, but fewer might be sufficient in some circumstances. An even distribution of sites among growth stages was less important than the total number of sites, and omission of species is unlikely to have a major influence on results as long as several species specialize on each growth stage. We highlight the importance of examining the responses of individual species to growth stage before feeding survey data into the growth-stage optimization black box, and advocate use of a resampling procedure to determine the precision of results. Collectively, our findings form a reproducible guide to designing ecological surveys that yield precise conservation targets through growth-stage optimization, and ultimately help sustain biodiversity in fire-prone systems.
Figure 1 from: Borisenko A, Young R, Hanner R (2024) A lab-centric, workflow-based data management system for environmental DNA research. Research Ideas and Outcomes 10: e120483. https://doi.org/10.3897/rio.10.e120483
Figure 1 Schematic representation of key ontological entities of an eDNA data management system.
Gentsch et al.:Soil nitrogen and water management by winter-killed catch crops. Open data and R scripts.
<p>The file contains metadata on catch crop biomass, soil water contents, and ammonia and nitrate contents in different soil depth from the CATCHY experimental field site Asendorf. R scripts are provided for statistic evaluation of the metadata, plots for publication and spatiotemporal visualization. The article to this data set ist published in the lournal SOIL from Copernicus publisher: <a href="https://soil.copernicus.org/articles/8/269/2022/">https://soil.copernicus.org/articles/8/269/2022/</a></p>
Model output data of the paper: "Management induced changes of soil organic carbon on global croplands"
<p># Model output data of the paper: "Management induced changes of soil organic carbon on global croplands"<br> This data was prodused using the the MadRat framework and the mrsoil R-library by the R-script SOCBudget.R, which is stored together with the data. mrsoil is based on the R-libraries mrcommons, mrmagpie and mrvalidation.</p> <p>### REFERENCES<br> Dietrich J, Baumstark L, Wirth S, Giannousakis A, Rodrigues R, Bodirsky B, Kreidenweis U, Klein D (2020). _madrat: May All Data be<br> Reproducible and Transparent (MADRaT)_. doi: 10.5281/zenodo.1115490 (URL: https://doi.org/10.5281/zenodo.1115490), R package version<br> 1.86.0, <URL: https://github.com/pik-piam/madrat>.</p> <p>rstens K, Dietrich J (2020). _mrsoil: MadRat Soil Organic Carbon Budget Library_. doi: 10.5281/zenodo.4317933 (URL:<br> https://doi.org/10.5281/zenodo.4317933), R package version 1.1.0, <URL: https://github.com/pik-piam/mrsoil>.</p> <p>Bodirsky B, Karstens K, Baumstark L, Weindl I, Wang X, Mishra A, Wirth S, Stevanovic M, Steinmetz N, Kreidenweis U, Rodrigues R, Popov<br> R, Humpenoeder F, Giannousakis A, Levesque A, Klein D, Araujo E, Beier F, Oeser J, Pehl M, Leip D, Molina Bacca E, Martinelli E,<br> Schreyer F, Dietrich J (2020). _mrcommons: MadRat commons Input Data Library_. doi: 10.5281/zenodo.3822009 (URL:<br> https://doi.org/10.5281/zenodo.3822009), R package version 0.11.10, <URL: https://github.com/pik-piam/mrcommons>.</p> <p>Karstens K, Dietrich J, Chen D, Windisch M, Alves M, Beier F, v. Jeetze P, Mishra A, Humpenoeder F (2020). mrmagpie: madrat based MAgPIE Input Data Library. doi: 10.5281/zenodo.4319612 (URL: https://doi.org/10.5281/zenodo.4319612), R package version 0.31.0, <URL: https://github.com/pik-piam/mrmagpie>.</p> <p>Bodirsky B, Wirth S, Karstens K, Humpenoeder F, Stevanovic M, Mishra A, Biewald A, Weindl I, Chen D, Molina Bacca E, Kreidenweis U, W. Yalew A, Humpenoeder<br> F, Wang X, Dietrich J (2020). _mrvalidation: madrat data preparation for validation purposes_. doi: 10.5281/zenodo.4317826 (URL:<br> https://doi.org/10.5281/zenodo.4317826), R package version 2.5.0, <URL: https://github.com/pik-piam/mrvalidation>.</p> <p>## LICENSE<br> This data is open-source: you can redistribute it and/or modify it under the terms of the **CC Attribution 4.0 International** as published by the Creative Commons Corporation at https://creativecommons.org/licenses/by/4.0/legalcode.</p> <p>## CONTACT<br> karstens@pik-potsdam.de</p>
Figure 2 from: Canhos D (2017) Data Management Plan: Brazil's Virtual Herbarium. Research Ideas and Outcomes 3: e14675. https://doi.org/10.3897/rio.3.e14675
Figure 2 - Information and data flows in the BVH system.
Figure 1 from: Canhos D (2017) Data Management Plan: Brazil's Virtual Herbarium. Research Ideas and Outcomes 3: e14675. https://doi.org/10.3897/rio.3.e14675
Figure 1 - System architecture of the BVH and supporting systems.
Figure 1 from: Neylon C (2017) Building a Culture of Data Sharing: Policy Design and Implementation for Research Data Management in Development Research. Research Ideas and Outcomes 3: e21773. https://doi.org/10.3897/rio.3.e21773
Figure 1 - The Institutional Analysis and Design framework adapted from (Ostrom 2005).
Exploring Data Management Challenges and Solutions in Agile Software Development: A Literature Review and Practitioner Survey
<p>This comprehensive dataset for the Systematic Literature Review (SLR) and the survey responses on "Exploring Data Management Challenges and Solutions in Agile Software Development: A Literature Review and Practitioner Survey" contains detailed information on selected studies in the SLR. It features research titles, abstracts, keywords, and authors, along with Scopus-extracted details. The dataset encompasses various data types, such as business, product, process, project, and operational, and details the distribution of these studies across major data management aspects, including integration, collection, quality, and analysis. Additionally, the dataset offers insights into the quality assessment of these studies and covers other data management aspects, providing definitions, challenges, and solutions. Furthermore, it includes studies used for search validation, presenting a comprehensive overview of the distribution of study years across different data management aspects. Additionally, the survey participants' responses (with any personal information redacted or masked) are included.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.